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Record W3173135615 · doi:10.2166/washdev.2021.039

Who does what and why? Examining intra-household water and sanitation decision-making and autonomy in Asutifi North, Ghana

2021· article· en· W3173135615 on OpenAlexaff
Elijah Bisung, Sarah Dickin

Bibliographic record

VenueJournal of Water Sanitation and Hygiene for Development · 2021
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsQueen's University
Fundersnot available
KeywordsSanitationAgency (philosophy)AutonomyEmpowermentHygienePsychological interventionBusinessSocioeconomicsEconomic growthEnvironmental planningPsychologySociologyGeographyPolitical scienceEconomicsEngineeringMedicineSocial science

Abstract

fetched live from OpenAlex

Abstract While under-researched in the water, sanitation and hygiene (WASH) sector, it is increasingly clear that women's agency is fundamental to addressing inequalities in many contexts. However, focusing on agency alone can overlook the underlying reasons for decision-making behaviour. This article examines two important aspects of decision-making: motivations behind a person's actions, and the extent to which decisions are perceived to be solely or jointly made. We draw on a household survey of 600 respondents to examine decision-making related to three domains: water collection, WASH expenditures, and WASH community planning among dual adult household members in Asutifi North district, Ghana. On average, women were more likely to report no input into decision-making related to sanitation expenditure and community participation. However, women had high decision-making autonomy related to water collection and community participation compared to men. Disagreement on decision-making among partners was substantial and systematic across the three domains. These findings imply that decision-making in WASH are gendered, and better contextual understanding of the underlying gender dynamics is very important for promoting women's empowerment in WASH. These dynamics are particularly important to consider in interventions that rely on household self-supply of water or sanitation facilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.264
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

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